This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.

Try executing this chunk by clicking the Run button within the chunk or by placing your cursor inside it and pressing Cmd+Shift+Enter.

#testing very variable threshold and steepness

#testing uniform

set.seed(123)

global.threshold<-90:90

global.steepness<-10:10

threshold.for.action<- 0.9

decay.rate<- 0.9

influencer.degree<- 25

test.network.3<-net.barabasi.albert(100,2, detectCores(), FALSE) %>%
  add_influencer(influencer.degree=influencer.degree, population=100)

draw.net.large.network(test.network.3, influencer=101)


test.3.connection.matrix<- initialize_matrix(matrix(,101,101), test.network.3, 101)

test.3.activation.matrix<- matrix(0,cycles,101) %>%
  activate_influencer(population=100) %>%
  update.rule(.,test.3.connection.matrix, population = 100)

test.3.data<- data.frame(test.3.activation.matrix) %>%
  gather(key="Node", value= "activation") %>%
  cbind.data.frame(cycle=rep(seq(1:100),101))

new.actions.each.cycle.plot(test.3.activation.matrix, 100)

plot.by.degree(test.3.data, test.3.connection.matrix, 100)
Ignoring unknown aesthetics: line

ridgeline.plot(test.3.data)

testing very high vs. low influencer degree high degree

set.seed(123)

global.threshold<-0:100

global.steepness<-10:100

threshold.for.action<- 0.9

decay.rate<- 0.9

influencer.degree<- 50

test.network.4<-net.barabasi.albert(100,2, detectCores(), FALSE) %>%
  add_influencer(influencer.degree=influencer.degree, population=100)

draw.net.large.network(test.network.4, influencer=101)


test.4.connection.matrix<- initialize_matrix(matrix(,101,101), test.network.4, 101)

test.4.activation.matrix<- matrix(0,cycles,101) %>%
  activate_influencer(population=100) %>%
  update.rule(.,test.4.connection.matrix, population = 100)

test.4.data<- data.frame(test.4.activation.matrix) %>%
  gather(key="Node", value= "activation") %>%
  cbind.data.frame(cycle=rep(seq(1:100),101))

new.actions.each.cycle.plot(test.4.activation.matrix, 100)

plot.by.degree(test.4.data, test.4.connection.matrix, 100)
Ignoring unknown aesthetics: line

#low degree

set.seed(123)

global.threshold<-0:100

global.steepness<-10:100

threshold.for.action<- 0.9

decay.rate<- 0.9

influencer.degree<- 10

test.network.5<-net.barabasi.albert(100,2, detectCores(), FALSE) %>%
  add_influencer(influencer.degree=influencer.degree, population=100)

draw.net.large.network(test.network.5, influencer=101)


test.5.connection.matrix<- initialize_matrix(matrix(,101,101), test.network.5, 101)

test.5.activation.matrix<- matrix(0,cycles,101) %>%
  activate_influencer(population=100) %>%
  update.rule(.,test.5.connection.matrix, population = 100)

test.5.data<- data.frame(test.5.activation.matrix) %>%
  gather(key="Node", value= "activation") %>%
  cbind.data.frame(cycle=rep(seq(1:100),101))

new.actions.each.cycle.plot(test.5.activation.matrix, 100)

plot.by.degree(test.5.data, test.5.connection.matrix, 100)
Ignoring unknown aesthetics: line

trying to create a scenario in which one post does not make all of them active

set.seed(234)

global.threshold<-50:60

global.steepness<-40:100

threshold.for.action<- 0.9

decay.rate<- 0.9

influencer.degree<- 25

test.network.6<- net.barabasi.albert(100,2,detectCores(), FALSE) %>%
  add_influencer(influencer.degree=influencer.degree, population=100)

draw.net.large.network(test.network.6, influencer=101)


test.6.connection.matrix<- initialize_matrix(matrix(,101,101), test.network.6, 101)

test.6.activation.matrix<- matrix(0,cycles,101) %>%
  activate_influencer(population=100) %>%
  update.rule(.,test.6.connection.matrix, population = 100)

test.6.data<- data.frame(test.6.activation.matrix) %>%
  gather(key="Node", value= "activation") %>%
  cbind.data.frame(cycle=rep(seq(1:100),101))

new.actions.each.cycle.plot(test.6.activation.matrix, 100)

plot.by.degree(test.6.data, test.6.connection.matrix, 100)
Ignoring unknown aesthetics: line

set.seed(123)

global.threshold<-50:60

global.steepness<-40:100

threshold.for.action<- 0.9

decay.rate<- 0.9

influencer.degree<- 25

test.network.7<- net.barabasi.albert(100,2,detectCores(), FALSE) %>%
  add_influencer(influencer.degree=influencer.degree, population=100)

draw.net.large.network(test.network.7, influencer=101)


test.7.connection.matrix<- initialize_matrix(matrix(,101,101), test.network.7, 101)

test.7.activation.matrix<- matrix(0,cycles,101) %>%
  activate_influencer(population=100) %>%
  multi.update.rule(.,test.7.connection.matrix, population = 100, c(10,25))

test.7.data<- data.frame(test.7.activation.matrix) %>%
  gather(key="Node", value= "activation") %>%
  cbind.data.frame(cycle=rep(seq(1:100),101))

new.actions.each.cycle.plot(test.7.activation.matrix, 100)

plot.by.degree(test.7.data, test.7.connection.matrix, 100)
Ignoring unknown aesthetics: line

```

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